Patent · US Active

Method for training an artificial neural network

US12380704B2 · kind B2 · utility

0Cited by

0References

12Claims

0Family size

Assignee

Robert Bosch GmbH · DE

Inventors

Carsten Hasberg · Ilsfeld, DE
Tayyab Naseer · London, GB
Piyapat Saranrittichai · Nuremberg, DE

Key dates

Filing date	May 4, 2021
Grant date	Aug 5, 2025
Priority date	—
Expiry date	Sep 1, 2042

Classification

Technology area (CPC G)Physics
CPC primaryG06T2207/20084
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

A method for training an artificial neural network uses training data that include first image data of a first image and second image data of a second image of an infrastructure. The first image includes a first feature, and the second image includes a second feature corresponding to the first image. The training data include a relative desired translation and a relative desired rotation between the first feature and the second feature. The training includes extracting the first feature from the first image and extracting the second feature from the second image using the artificial neural network. The extracted first feature is represented by first feature data having a first volume of data. The extracted second feature is represented by second feature data having a second volume of data. The training further includes ascertaining a relative translation and a relative rotation between the extracted first feature and the extracted second.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.